Non-transitory computer-readable medium, information classification method, and information processing apparatus

ABSTRACT

There is provided a non-transitory computer-readable medium storing a program causing a computer to execute a process. The process includes: accepting a search keyword; retrieving, from information items posted by users, a posted information item including the accepted search keyword, each of the posted information items including at least either of a text information item and an image information item, and acquiring posted information items which are within a predetermined chronological range with respect to the posted information item including the search keyword; and classifying, as image information items related to the search keyword, some of image information items included in the posted information items that have been acquired, and performing first determination of, for each of the classified image information items, whether or not a user who posted an information item including the classified image information item took an action related to the search keyword.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2012-196417 filed Sep. 6, 2012.

BACKGROUND Technical Field

The present invention relates to a non-transitory computer-readablemedium, an information classification method, and an informationprocessing apparatus.

SUMMARY

According to an aspect of the invention, there is provided anon-transitory computer-readable medium storing a program causing acomputer to execute a process. The process includes the following:accepting a search keyword; retrieving, from multiple information itemsposted by multiple users, a posted information item including theaccepted search keyword, each of the multiple posted information itemsincluding at least either of a text information item and an imageinformation item, and acquiring posted information items which arewithin a predetermined chronological range with respect to the postedinformation item including the search keyword; and classifying, as imageinformation items related to the search keyword, some of imageinformation items included in the posted information items that havebeen acquired, and performing first determination of, for each of theclassified image information items, whether or not a user who posted aninformation item including the classified image information item took anaction related to the search keyword.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention will be described indetail based on the following figures, wherein:

FIG. 1 is a block diagram illustrating an example of a configuration ofa microblog classification system according to an exemplary embodimentof the present invention;

FIG. 2 is a block diagram illustrating an example of a configuration ofa microblog classification server;

FIG. 3 is a schematic diagram illustrating an example of a configurationof microblog information items;

FIG. 4 is a schematic diagram illustrating an example of a configurationof microblog image information items;

FIG. 5 is a schematic diagram illustrating an example of a configurationof microblog text information items;

FIG. 6 is a schematic diagram illustrating an example of a configurationof an image list display screen that is displayed on a display of aterminal by an image list display unit;

FIG. 7 is a schematic diagram illustrating an example of a configurationof classification-result information items;

FIG. 8 is a schematic diagram illustrating an example of a configurationof a display screen that is output by a classification-result outputunit on the basis of the classification-result information items;

FIG. 9 is a flowchart illustrating an example of an operation of themicroblog classification server in the case of generating an imageclassification model;

FIG. 10 is a flowchart illustrating an example of an operation of themicroblog classification server in the case of acquiring the microbloginformation items;

FIG. 11 is a flowchart illustrating an example of an operation of themicroblog classification server in the case of determining whether ornot a user who posted an information item, which is referred to as aposted information item, took an action; and

FIG. 12 is a flowchart illustrating an example of an operation of themicroblog classification server in the case of determining whether thecontent of a posted information item is positive or negative.

DETAILED DESCRIPTION Exemplary Embodiment

Configuration of Microblog Classification System

FIG. 1 is a schematic diagram illustrating an example of a configurationof a microblog classification system according to an exemplaryembodiment of the present invention.

A microblog classification system 6 includes a microblog classificationserver 1, a microblog server 2, a terminal 3, and a terminal 4, andconnects, using a network 5, the individual apparatuses so that theapparatuses are able to communicate with each other. Here, a microblogis a medium in which multiple text information items and imageinformation items that were posted (transmitted) are mixed and displayedin chronological order. More specifically, microblog information itemsstored in the microblog server 2 are subjected to a display process byan information processing apparatus such as the terminal 3 or 4, wherebythe microblog is displayed. Hereinafter, the unit of an information itemposted on the microblog is referred, for simplicity, to as a “postedinformation item”. It is supposed that a posted information itemincludes a text information item and an image information item, includesonly a text information item, or includes only an image informationitem. In other words, each of the microblog information items includesmultiple posted information items. Furthermore, posted information itemsare information items posted by multiple users.

The microblog classification server 1 is an information processingapparatus that includes electronic components such as a centralprocessing unit (CPU) having functions for processing information itemsand a memory. The microblog classification server 1 accepts a searchkeyword, acquires posted information items related to the search keywordfrom the microblog server 2, and classifies the acquired postedinformation items. Each of the acquired posted information items isclassified by determining whether or not a user who posted theinformation item that has been acquired as a posted information itemtook an action related to the search keyword, and by determining whetherthe content of the posted information item that has been acquired ispositive (favorable) or negative (unfavorable).

The microblog server 2 is an information processing apparatus thatincludes electronic components such as a CPU having functions forprocessing information items and a memory. The microblog server 2accepts text information items such text items and/or image informationitems concerning still images such as photographs or moving images,which have been transmitted from the terminal 4 or the like and whichare to be referred to as posted information items, and generatesmicroblog information items for displaying the posted information itemsin chronological order. Moreover, when the microblog server 2 accepts,from the terminal 4, a request to view the microblog information items,the microblog server 2 transmits the microblog information items to theterminal 4. Note that it is supposed that an image information itemincluded in a posted information item directly includes an informationitem concerning a still image or a moving image or includes a linkdestination information item concerning a link destination in which aninformation item concerning a still image or a moving image is stored.Furthermore, a text information item included in a posted informationitem may directly include an information item concerning a text item ormay include a link destination information item concerning a linkdestination in which an information item concerning a text file, ahypertext markup language (HTML) file, or the like is stored.

The terminal 3 includes an operation unit such as a keyboard or mouseused to input an instruction for an operation, a display such as aliquid crystal display, a controller such as a CPU having functions forprocessing information items, and a memory such as a hard disk drive(HDD). The terminal 3 accepts a search keyword input from a user,transmits the search keyword to the microblog classification server 1,and requests the microblog classification server 1 to performclassification of the microblog information items. When classificationresults are output from the microblog classification server 1, theterminal 3 receives the classification results, and displays theclassification results on the display.

Note that the terminal 3 is, for example, a personal computer.Alternatively, a mobile phone, a personal digital assistant (PDA), orthe like may be used as the terminal 3. Furthermore, although oneterminal 3 is illustrated in FIG. 1, the number of terminals 3 may betwo or more.

The terminal 4 includes an operation unit such as a touch panel used toinput an instruction for an operation, a display such as a liquidcrystal display provided under the touch panel, and a controller havingelectronic components such as a CPU and a memory. The terminal 4transmits an information item, which is to be referred to as a postedinformation item, such as a text item or an image, to the microblogserver 2 in accordance with an operation performed by a user, therebyposting the information item on the microblog. Moreover, the terminal 4transmits, to the microblog server 2, in accordance with an operationperformed by the user, a request to view the microblog. When theterminal 4 receives the microblog information items from the microblogserver 2 as a result of the request to view the microblog, the terminal4 displays, on the display, text items or images (still images or movingimages) included in posted information items of the microblog.

Note that the terminal 4 is, for example, a mobile phone. Alternatively,a PDA, a personal computer, or the like may be used as the terminal 4.Furthermore, although one terminal 4 is illustrated in FIG. 1, thenumber of terminals 4 may be two or more.

The network 5 is a communication network such as the Internet or a localarea network (LAN), regardless of whether the network 5 is a wirednetwork or wireless network.

Configuration of Microblog Classification Server

FIG. 2 is a block diagram illustrating an example of a configuration ofthe microblog classification server 1.

The microblog classification server 1 includes a controller 10, a memory11, and a communication section 12. The controller 10 is constituted bya CPU or the like, and controls individual units and executes varioustypes of programs. The memory 11 is provided as an example of a storagedevice that is constituted by a recording medium such as an HDD or aflash memory and that stores information items. The communicationsection 12 communicates with an external apparatus via the network 5.

The controller 10 executes a microblog classification program 110, whichis described below, thereby functioning as an image list display unit100, a related-image selection unit 101, an image-classification-modelgenerating unit 102, a search-keyword accepting unit 103, amicroblog-information acquisition unit 104, an image-informationclassification unit 105, a text-information classification unit 106, anaction taken/not-taken determination unit 107, a positive/negativedetermination unit 108, a classification-result output unit 109, and soforth.

The image list display unit 100 generates, for all or a predeterminednumber of microblog information items that have been acquired by themicroblog-information acquisition unit 104 described below, aninformation item for performing list display of image information itemsincluded in the microblog information items on the display of theterminal 3, and transmits the generated information item to the terminal3.

In a state in which the information item generated by the image listdisplay unit 100 is displayed on the display of the terminal 3, therelated-image selection unit 101 selects, in accordance with anoperation performed by the user of the terminal 3, some images from theimages that are being displayed.

The image-classification-model generating unit 102 extracts, as learningdata items of positive examples, feature values from the images selectedby the related-image selection unit 101. The image-classification-modelgenerating unit 102 extracts, as learning data items of negativeexamples, feature values from images that are not selected by therelated-image selection unit 101. The image-classification-modelgenerating unit 102 generates, using the learning data items, an imageclassification model 114 in relation to a search keyword accepted by thesearch-keyword accepting unit 103. Note that a generating method will bedescribed below.

The search-keyword accepting unit 103 accepts a search keyword from theterminal 3.

The microblog-information acquisition unit 104 acquires, from themicroblog server 2, microblog information items 111 related to thesearch keyword accepted by the search-keyword accepting unit 103, andstores the microblog information items 111 in the memory 11. Note thatthe microblog information items 111 may be acquired from all of themicroblog information items accumulated in the microblog server 2, ormay be acquired from microblog information items that have been obtainedby filtering using a predetermined time period, a predetermined keyword,or the like. A method for acquiring the microblog information items 111will be described below.

The image-information classification unit 105 stores information itemsthat have been obtained by removing text information items fromindividual posted information items included in the microbloginformation items 111 acquired by the microblog-information acquisitionunit 104, i.e., only image information items, as microblog imageinformation items 112 in the memory 11.

The text-information classification unit 106 stores information itemsthat have been obtained by removing image information items from theindividual posted information items included in the microbloginformation items 111 acquired by the microblog-information acquisitionunit 104, i.e., text information items, as microblog text informationitems 113 in the memory 11.

The action taken/not-taken determination unit 107 determines, on thebasis of the image classification model 114, for each of the microblogimage information items 112, whether or not a user who posted aninformation item including the microblog image information item 112 tookan action related to the search keyword accepted by the search-keywordaccepting unit 103, and stores an action taken/not-taken determinationresult 116 in the memory 11. Note that, when the microblog imageinformation item 112 matches the image classification model 114, theaction taken/not-taken determination unit 107 determines that the usertook the action. Furthermore, for each of the microblog text informationitems 113, when the microblog text information item 113 does not match atext classification model 115 that is prepared, the actiontaken/not-taken determination unit 107 determines that the user did nottake the action. Specific determination methods will be described below.Additionally, a second text classification model may be provided, and,for each of the microblog text information items 113, when the microblogtext information item 113 matches the second text classification model,the action taken/not-taken determination unit 107 may determine that theuser took the action.

The positive/negative determination unit 108 determines, on the textclassification model 115, for each of the microblog text informationitems 113, whether the content of a posted information item includingthe microblog text information item 113 is positive (favorable) ornegative (unfavorable), and stores a positive/negative determinationresult 117 in the memory 11. Note that, the text classification model115 used by the positive/negative determination unit 108 is learned fromfeature vectors, for example, each of which represents thepresence/absence of individual words as an element in text items thateach belong to a positive group or a negative group. Thepositive/negative determination unit 108 generates a feature vectorsimilarly for a text information item that is a classification target,and compares the generated feature vector with the feature vectorsobtained as a result of learning. Accordingly, the text information itemthat is a classification target is classified by determining whether thetext information item belongs to the positive group or the negativegroup. Furthermore, the positive/negative determination unit 108 maydetermine, on the basis of each of the microblog image information items112, whether the content of a posted information item including themicroblog image information item 112 is positive or negative.

The classification-result output unit 109 generatesclassification-result information items 118 from the actiontaken/not-taken determination results 116 and the positive/negativedetermination results 117, and outputs the classification-resultinformation items 118 to an external apparatus, e.g., the terminal 3.

The memory 11 stores the microblog classification program 110, themicroblog information items 111, the microblog image information items112, the microblog text information items 113, the image classificationmodel 114, the text classification model 115, the action taken/not-takendetermination results 116, the positive/negative determination results117, the classification-result information items 118, and so forth.

The microblog classification program 110 is a program that causes thecontroller 10 to operate as the above-described individual units 100 to108.

It is supposed that the image classification model 114 has, as differentinformation items, information items used by the action taken/not-takendetermination unit 107 and information items used by thepositive/negative determination unit 108. Furthermore, it is supposedthat, similarly, the text classification model 115 also has, asdifferent information items, information items used by the actiontaken/not-taken determination unit 107 and information items used by thepositive/negative determination unit 108. Note that the imageclassification model 114 is not limited to an image classification modelgenerated by the image-classification-model generating unit 102. A modelprepared in the memory 11 may be used as the image classification model114, or a configuration in which a model prepared in an external unit isacquired as the image classification model 114 may be used.

FIG. 3 is a schematic diagram illustrating an example of a configurationof the microblog information items 111.

The microblog information items 111 have a user ID column, a microblogID column, and a content column. In the user ID column, identifiers ofusers who posted information items that are referred to as postedinformation items are arranged. In the microblog ID column, for example,identifiers that are added in chronological order are arranged. In thecontent column, content items that are text items input as the postedinformation items, URLs of other servers in which images (still imagesor moving images) are stored and which are not illustrated, or the textitems and the URLs are arranged. Note that, instated of the URLsarranged in the content column, information items concerning the stillimages or the moving images may be directly arranged in the contentcolumn.

Note that, although each of the content items includes a timeinformation item indicating a time at which the content item was posted,here, the time information item is omitted and the content item isdisplayed.

FIG. 4 is a schematic diagram illustrating an example of a configurationof the microblog image information items 112.

The microblog image information items 112 have a user ID column, amicroblog ID column, and an image content column. The user ID column andthe microblog ID column are same as the user ID column and the microblogID column illustrated in FIG. 3. In the image content column, actualimage information items stored in URLs which were input as postedinformation items are arranged.

In other words, the microblog image information items 112 are obtainedby removing, from the microblog information items 111, postedinformation items including only text items, and by acquiring imageinformation items from URLs in which images are stored.

FIG. 5 is a schematic diagram illustrating an example of a configurationof the microblog text information items 113.

The microblog text information items 113 have a user ID column, amicroblog ID column, and a text content column. The user ID column andthe microblog ID column are the same as user ID column and the microblogID column illustrated in FIG. 3. In the text content column, contentitems that are text items which were input as posted information itemsare arranged.

In other words, the microblog text information items 113 are obtained byremoving, from the microblog information items 111, posted informationitems including only URLs in which images are stored, and by removingURLs from the remaining posted information items.

Operation of Microblog Classification System

Next operations in the present exemplary embodiment are separatelydescribed as the following operations: (1) basic operation; (2)image-classification-model generating operation; (3)microblog-information acquiring operation; (4) action taken/not-takendetermination operation; (5) positive/negative determination operation;and (6) classification-result output operation.

(1) Basic Operation

First, the user of the terminal 4 performs, on the terminal 4, anoperation for transmitting an information item, which is to be referredto as a posted information item, to the microblog. Note that thefollowing operation may be performed on the terminal 3.

The terminal 4 transmits, to the microblog server 2, in accordance withthe operation performed by the user, an information item which includesa text item, an image, or the like and which is to be referred to as aposted information item, thereby posting the information item on themicroblog.

The microblog server 2 receives the posted information item from theterminal 4, thereby accumulating the microblog information items.

Furthermore, the user of the terminal 4 performs, on the terminal 4, anoperation for viewing the microblog.

The terminal 4 transmits, to the microblog server 2, in accordance withthe operation performed by the user, a request to view the microbloginformation items.

The microblog server 2 transmits the microblog information items to theterminal 4.

When the terminal 4 receives the microblog information items from themicroblog server 2, the terminal 4 displays, on the display, text itemsor images posted on the microblog.

Next, an operation for generating an image classification model will bedescribed as an operation that is preparatory to classification of themicroblog information items.

(2) Image-Classification-Model Generating Operation

FIG. 9 is a flowchart illustrating an example of an operation of themicroblog classification server 1 in the case of generating the imageclassification model 114.

First, the image list display unit 100 acquires, among the microbloginformation items acquired by the microblog-information acquisition unit104, all of the microblog information items or a predetermined number ofmicroblog information items (S1). The image list display unit 100generates an information item for performing list display of imageinformation items included in the microblog information items on thedisplay of the terminal 3, and transmits the generated information itemto the terminal 3 (S2).

The terminal 3 receives the information item, and displays an image listdisplay screen on the display.

FIG. 6 is a schematic diagram illustrating an example of a configurationof an image list display screen that is displayed on the display of theterminal 3 by the image list display unit 100.

In an image list display screen 103 a, list display of multiple images112 ₁, 112 ₂, . . . is performed. Note that the image list displayscreen 103 a may be displayed in multiple pages.

Next, the user operates the operation unit of the terminal 3 withreference to the image list display screen 103 a, thereby selectingcertain images. The details of the operation are transmitted from theterminal 3 to the microblog classification server 1. Here, for example,it is supposed that the user selects images related to a keyword of “ABCfireworks display”, i.e., images including fireworks, images includingshop stands, images including people wearing yukatas that are Japanesegarments, and so forth.

Next, the related-image selection unit 101 of the microblogclassification server 1 accepts the details of the operation. In a statein which the information item generated by the image list display unit100 is displayed on the display of the terminal 3, the related-imageselection unit 101 selects, in accordance with the operation performedby the user of the terminal 3, some images from the images that arebeing displayed (S3). The selected images are in a state of beingselected using a selection frame 103 b as illustrated in FIG. 6.

Next, the image-classification-model generating unit 102 extractsfeature values of the images selected by the related-image selectionunit 101, and generates learning data items of the positive examples(S4).

Next, the image-classification-model generating unit 102 extractsfeature values of the images that are not selected by the related-imageselection unit 101, and generates learning data items of the negativeexamples (S5). Note that classification of the images is not limited toclassification into two groups that are the positive example and thenegative example, and may be classification into multiple groups.

Next, the image-classification-model generating unit 102 generates theimage classification model 114 from the learning data items of thepositive examples and the learning data items of the negative examplesin relation to the search keyword (“ABC fireworks display”) accepted bythe search-keyword accepting unit 103 described below (S6), and storesthe image classification model 114 in the memory 11 (S7).

Meanwhile, in order to make a request of the microblog classificationserver 1 to classify the microblog information items, the user of theterminal 3 operates the operation unit of the terminal 3, therebyinputting a search keyword. The terminal 3 transmits, together with therequest to classify the microblog information items, the search keywordto the microblog classification server 1.

The microblog classification server 1 operates as follows in response tothe request.

(3) Microblog-Information Acquiring Operation

FIG. 10 is a flowchart illustrating an example of an operation of themicroblog classification server 1 in the case of acquiring the microbloginformation items.

First, the search-keyword accepting unit 103 accepts the search keywordof “ABC fireworks display” from the terminal 3 (S10).

Next, the microblog-information acquisition unit 104 retrieves postedinformation items on the basis of the search keyword accepted by thesearch-keyword accepting unit 103 from the microblog information itemsstored in the microblog server 2 (S11). Note that, in the case ofretrieving posted information items, posted information items completelyincluding “ABC fireworks display” may be retrieved. In addition, anabbreviation of the search keyword or multilingual versions of thekeyword may be used, or posted information items may be retrieved usingmultiple keywords.

Next, the microblog-information acquisition unit 104 extracts user IDsof the posted information items which include the search keyword andwhich have been retrieved as search results (S12), and acquires, foreach of the extracted user IDs, posted information items that wereposted by the user ID (S13). Note that all posted information items thatwere posted by the user ID may be acquired, or, for each of the postedinformation items including the search keyword, posted information itemsthat are within a predetermined chronological range with respect to theposted information item including the search keyword may be acquired.

Next, when link URLs indicating links to image information items areincluded in the posted information items that have been acquired, themicroblog-information acquisition unit 104 acquires the imageinformation items stored in the link URLs (S15).

Steps S13 to S15 described above are performed for all of the user IDsextracted in step S12.

Next, the microblog classification server 1 operates as follows so as todetermine whether or not an action related to the search keyword wastaken.

(4) Action Taken/not-Taken Determination Operation

FIG. 11 is a flowchart illustrating an example of an operation of themicroblog classification server 1 in the case of determining whether ornot a user who posted information items that are referred to as postedinformation items took an action.

First, the action taken/not-taken determination unit 107 acquires postedinformation items of a certain user ID (S20).

Next, the image-information classification unit 105 considers only imageinformation items of the certain user ID as the microblog imageinformation items 112 (S22). The action taken/not-taken determinationunit 107 determines whether or not each of images included in themicroblog image information items 112 matches the positive example ofthe image classification model 114 (S23 and S24). In other words, theaction taken/not-taken determination unit 107 classifies some of themicroblog image information items 112 as image information items relatedto the search keyword. As a result of classification, for each of theclassified microblog image information items 112, when the classifiedmicroblog image information item 112 matches the positive example (YESin S23), the action taken/not-taken determination unit 107 determinesthat the user having the user ID “took the action” related to the searchkeyword (S24). Note that, in the case where the search keyword is “ABCfireworks display”, the phrase “took the action” indicates, for example,that a user “attended to the ABC fireworks display”. Here, it issupposed that “classification as image information items related to thesearch keyword” includes not only classification as image informationitems which match the image classification model 114 generated in “(2)image-classification-model generating operation”, but alsoclassification as image information items which match a model preparedin the memory 11 or a model prepared in an external unit.

Note that, in step S24, in the case where, for the same user ID, thenumber of images that match the positive example is equal to or largerthan a predetermined threshold, the action taken/not-taken determinationunit 107 may determine that the user having the user ID “took theaction”.

Next, when, in step S23, the classified microblog image information item112 does not match the positive example (NO in S23), whether or not theuser having the user ID took the action is still “unknown”. Accordingly,next, classification based on text information items is performed. Thetext-information classification unit 106 considers, as the microblogtext information items 113, only text information items included in theposted information items, which have been acquired by the actiontaken/not-taken determination unit 107, of the certain user ID (S26).The action taken/not-taken determination unit 107 determines whether ornot each of the microblog text information items 113 matches the textclassification model 115 (S27 and S28). When the microblog textinformation item 113 does not match the text classification model 115(NO in S27), the action taken/not-taken determination unit 107determines that the user having the user ID did “not take the action”(S29). Note that, in the case where the search keyword is “ABC fireworksdisplay”, the phrase “not take the action” indicates, for example, thata user did “not attend to the ABC fireworks display”.

Note that determination of whether or not the action was taken, which isdescribed above, is performed for all user IDs (S30), and determinationresults are stored as the action taken/not-taken determination results116 in the memory 11.

Next, the microblog classification server 1 operates as follows so as todetermine whether the content of a posted information item is positiveor negative.

(5) Positive/Negative Determination Operation

FIG. 12 is a flowchart illustrating an example of an operation of themicroblog classification server 1 in the case of determining whether thecontent of a posted information item is positive or negative.

First, the positive/negative determination unit 108 acquires postedinformation items of a certain user ID (S40).

The text-information classification unit 106 considers, as the microblogtext information items 113, only text information items included in theposted information items, which have been acquired by thepositive/negative determination unit 108, of the certain user ID (S41).The positive/negative determination unit 108 determines whether thecontent of each of the microblog text information items 113 is positiveor negative (S42 and S43). Note that, in the case where the searchkeyword is “ABC fireworks display”, the term “positive” indicates, forexample, a favorable opinion about the “ABC fireworks display”, and theterm “negative” indicates, for example, an unfavorable opinion about the“ABC fireworks display”.

Note that determination of whether or not the content of a textinformation item is positive or negative, which is described above, isperformed for all user IDS (S44), and determination results are storedas the positive/negative determination results 117 in the memory 11.

(6) Classification-Result Output Operation

Next, the classification-result output unit 109 generates theclassification-result information items 118 from the actiontaken/not-taken determination results 116 and the positive/negativedetermination results 117, and transmits the classification-resultinformation items 118 to the terminal 3.

FIG. 7 is a schematic diagram illustrating an example of a configurationof the classification-result information items 118.

The classification-result information items 118 have a user ID column, amicroblog ID column, a content column, an image content column, anaction taken/not-taken determination result column, and apositive/negative determination result column. The user ID column, themicroblog ID column, and the content column are the user ID column, themicroblog ID column, and the content column illustrated in FIG. 3, whichare provided as common columns. The image content column is the imagecontent column illustrated in FIG. 5, which is provided as a commoncolumn. In the action taken/not-taken determination result column, thedetermination results obtained by the action taken/not-takendetermination unit 107 are arranged. In the positive/negativedetermination result column, the determination results obtained by thepositive/negative determination unit 108 are arranged.

Note that determination of whether or not an action was taken isperformed for each user ID, and determination of whether the content ofa text information item is positive or negative is performed for eachposted information item.

Furthermore, the terminal 3 may receive the classification-resultinformation items 118, and may display the following information itemson the display.

FIG. 8 is a schematic diagram illustrating an example of a configurationof a display screen that is output by the classification-result outputunit 109 on the basis of the classification-result information items118.

A classification-result-information display screen 108 a includescontent items 108 b ₁ and an image 108 c ₁, content items 108 b ₂,content items 108 b ₃ and an image 108 c ₃, and content items 108 b ₄.The content items 108 b ₁ and the image 108 c ₁ are posted informationitems, and each of the posted information items indicates, for theaction, that a user “attended the fireworks display” and the content ofthe posted information item is “positive”. The content items 108 b ₂ areposted information items, and each of the posted information itemsindicates, for the action, that a user did “not attend the fireworksdisplay” and the content of the posted information item is “positive”.The content items 108 b ₃ and the image 108 c ₃ are posted informationitems, and each of the posted information items indicates, for theaction, that a user “attended the fireworks display” and the content ofthe posted information item is “negative”. The content items 108 b ₄ areposted information items, and each of the posted information itemindicates, for the action, that a user did “not attend the fireworksdisplay” and the content of the posted information item is “negative”.

In the foregoing exemplary embodiment, each of the microblog imageinformation items 112 is classified on the basis of the imageclassification model 114, and whether or not a user who posted aninformation item including the classified image information item took anaction related to a search keyword is determined. Additionally, each ofthe microblog text information items 113 is classified on the basis ofthe text classification model 115, and whether or not a user who postedan information item including the classified text information item tookthe action related to the search keyword is determined. Accordingly, aposted information item may be classified by determining whether or nota user who posted the information item took the action.

Furthermore, each of the microblog text information items 113 includedin posted information items is classified on the basis of the textclassification model 115, and whether the content of a postedinformation item including the classified text information item isfavorable or unfavorable is determined. Accordingly, a postedinformation item may be classified by determining whether the content ofthe posted information item is positive or negative.

Moreover, classification results are displayed as in theclassification-result-information display screen 108 a illustrated inFIG. 8. Accordingly, for example, the attractive points of the “ABCfireworks display” may be extracted from the content items 108 b ₁ andthe image 108 c ₁. For example, points for causing users to attend the“ABC fireworks display” may be extracted from the content items 108 b ₁and the image 108 c ₁, and the content items 108 b ₂. Improvement pointsof the “ABC fireworks display” may be extracted from the content items108 b ₃ and the image 108 c ₃. Points for improving the impression ofthe “ABC fireworks display” may be extracted from the content items 108b ₄. Furthermore, a statistical information item concerning theclassification-result information items 118 illustrated in FIG. 7 may begenerated and output. Moreover, distribution of information items toindividual users on the basis of the classification-result informationitems 118 may be performed. More specifically, for example,advertisements are distributed to users who attended the “ABC fireworksdisplay” and users who did not attend the “ABC fireworks display” insuch a manner that the content of the advertisement distributed to theusers who attended the “ABC fireworks display” and the content of theadvertisement distributed to the users who did not attend the “ABCfireworks display” are different from each other.

Other Exemplary Embodiments

Note that the present invention is not limited to the foregoingexemplary embodiment, and various modifications may be made withoutdeparting from the scope of the present invention. For example, themicroblog is not limited to Twitter (registered trademark), and any typeof medium may be used if the medium is a medium on which comparativelyshort text items are posted, in which text information items and imageinformation items (including still images, moving images, and linkdestination information items concerning links to information itemsconcerning the still images or moving images) are mixed, and in which alarge number of text information items and image information items aredisplayed in chronological order, such as Facebook (registeredtrademark). Furthermore, messages or the like of mail may be targets tobe processed.

In the foregoing exemplary embodiment, the functions of the individualunits 100 to 108 included in the controller 10 are realized by aprogram. However, all or some of the individual units may be realized byhardware such as an application-specific integrated circuit (ASIC).Furthermore, the program used in the foregoing exemplary embodiment maybe stored on a recording medium, such as a compact disc read-only memory(CD-ROM), and supplied. Moreover, the steps described in the foregoingexemplary embodiment may be, for example, replaced, removed, or addedwithout changing the scope of the present invention.

The foregoing description of the exemplary embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Obviously, many modificationsand variations will be apparent to practitioners skilled in the art. Theembodiments were chosen and described in order to best explain theprinciples of the invention and its practical applications, therebyenabling others skilled in the art to understand the invention forvarious embodiments and with the various modifications as are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

What is claimed is:
 1. A non-transitory computer-readable medium storinga program causing a computer to execute a process, the processcomprising: accepting a search keyword; retrieving, from a plurality ofinformation items posted by a plurality of users, a posted informationitem including the accepted search keyword, each of the plurality ofposted information items including at least either of a text informationitem and an image information item, and acquiring posted informationitems which are within a predetermined chronological range with respectto the posted information item including the search keyword;classifying, as image information items related to the search keyword,some of image information items included in the posted information itemsthat have been acquired, and performing first determination of, for eachof the classified image information items, whether or not a user whoposted an information item including the classified image informationitem took an action related to the search keyword by comparing each ofthe classified image information items to an image classification model,where each first determination for one of the classified imageinformation items makes the determination by examining a plurality ofthe classified image information items; and determining whether theimage classification model matches the classified image informationitem, wherein if the image classification model matches the classifiedimage information item, it is determined that the user took an actionthat includes posting the information item.
 2. The medium according toclaim 1, wherein, in the acquiring, a posted information item includingthe search keyword is retrieved from the plurality of posted informationitems, and, among other posted information items of a user who postedthe information item including the search keyword, posted informationitems that are within a predetermined chronological range with respectto the posted information item including the search keyword areacquired.
 3. The medium according to claim 1, wherein, in theclassifying and performing first determination, text information itemsincluded in the posted information items that have been acquired areclassified, and, for each of the classified text information items,whether or not a user who posted an information item including theclassified text information item took the action related to the searchkeyword is determined.
 4. The medium according to claim 2, wherein, inthe classifying and performing first determination, text informationitems included in the posted information items that have been acquiredare classified, and, for each of the classified text information items,whether or not a user who posted an information item including theclassified text information item took the action related to the searchkeyword is determined.
 5. The medium according to claim 1, the processfurther comprising classifying text information items included in theposted information items that have been acquired, and, performing seconddetermination of, for each of the classified text information items,whether the content of a posted information item including theclassified text information item is favorable or unfavorable.
 6. Themedium according to claim 2, the process further comprising classifyingtext information items included in the posted information items thathave been acquired, and, performing second determination of, for each ofthe classified text information items, whether the content of a postedinformation item including the classified text information item isfavorable or unfavorable.
 7. The medium according to claim 3, theprocess further comprising classifying text information items includedin the posted information items that have been acquired, and, performingsecond determination of, for each of the classified text informationitems, whether the content of a posted information item including theclassified text information item is favorable or unfavorable.
 8. Themedium according to claim 4, the process further comprising classifyingtext information items included in the posted information items thathave been acquired, and, performing second determination of, for each ofthe classified text information items, whether the content of a postedinformation item including the classified text information item isfavorable or unfavorable.
 9. The medium according to claim 5, wherein,in the classifying and performing second determination, imageinformation items included in the posted information items that havebeen acquired are classified, and, for each of the classified imageinformation items, whether the content of a posted information itemincluding the classified image information item is favorable orunfavorable is determined.
 10. The medium according to claim 6, wherein,in the classifying and performing second determination, imageinformation items included in the posted information items that havebeen acquired are classified, and, for each of the classified imageinformation items, whether the content of a posted information itemincluding the classified image information item is favorable orunfavorable is determined.
 11. The medium according to claim 7, wherein,in the classifying and performing second determination, imageinformation items included in the posted information items that havebeen acquired are classified, and, for each of the classified imageinformation items, whether the content of a posted information itemincluding the classified image information item is favorable orunfavorable is determined.
 12. The medium according to claim 8, wherein,in the classifying and performing second determination, imageinformation items included in the posted information items that havebeen acquired are classified, and, for each of the classified imageinformation items, whether the content of a posted information itemincluding the classified image information item is favorable orunfavorable is determined.
 13. An information classification methodcomprising: accepting a search keyword; retrieving, from a plurality ofinformation items posted by a plurality of users, a posted informationitem including the accepted search keyword, each of the plurality ofposted information items including at least either of a text informationitem and an image information item, and acquiring posted informationitems which are within a predetermined chronological range with respectto the posted information item including the search keyword;classifying, as image information items related to the search keyword,some of image information items included in the posted information itemsthat have been acquired, and performing first determination of, for eachof the classified image information items, whether or not a user whoposted an information item including the classified image informationitem took an action related to the search keyword by comparing each ofthe classified image information items to an image classification model,where each first determination for one of the classified imageinformation items makes the determination by examining a plurality ofthe classified image information items; and determining whether theimage classification model matches the classified image informationitem, wherein if the image classification model matches the classifiedimage information item, it is determined that the user took an actionthat includes posting the information item.
 14. An informationprocessing apparatus comprising: a processor and a memory, the memorystoring a processor executable program, the processor executable programbeing configured to: accept a search keyword; retrieve, from a pluralityof information items posted by a plurality of users, a postedinformation item including the search keyword accepted by the acceptingunit, each of the plurality of posted information items including atleast either of a text information item and an image information item,and that acquires posted information items which are within apredetermined chronological range with respect to the posted informationitem including the search keyword; classifies, as image informationitems related to the search keyword, some of image information itemsincluded in the posted information items acquired by the acquisitionunit, and that performs first determination of, for each of theclassified image information items, whether or not a user who posted aninformation item including the classified image information item took anaction related to the search keyword by comparing each of the classifiedimage information items to an image classification model, where eachfirst determination for one of the classified image information itemsmakes the determination by examining a plurality of the classified imageinformation items; and determining whether the image classificationmodel matches the classified image information item, wherein if theimage classification model matches the classified image informationitem, it is determined that the user took an action that includesposting the information item.